1. Field
The present disclosure relates generally to a data processing system and more particularly to a system for knowledge discovery and context management. Still more particularly, the present disclosure relates to a system for discovery and representation of knowledge and semantic relationships from data.
2. Background
Information overload refers to an excess amount of information being provided, which complicates processing and absorbing information. As available information increases, addressing information overload has become a significant challenge. Tools which increase access to information also contribute to information overload. In an information-rich environment, increasing availability to information decreases the amount of attention an information consumer can allocate to individual pieces of information.
Retrieval of specific information stored across disparate data sets and data types can be inefficient. Data is stored in many disparate types of structures, such as relational databases, extensible markup language documents, spreadsheets, electronic messages, really simple syndication (RSS) feeds, and others, for example. Querying across a whole collection of data requires querying each disparate type of resource individually. Additionally, each resource may have its own query language or style. Summarizing the results of these individual searches may take significant time and effort, as well as being cost-prohibitive.
Another aspect of information is the potential to be ambiguous. Terminology is often understood in different ways by different consumers, and may also be understood differently based on context. Data is useful when the information it contains can be discovered or extracted in some efficient and transparent manner. Discovering information from data requires querying across a collection of data and aligning information to a given context as well as capturing its relationship to other information.
Therefore, it is advantageous to have a method and apparatus that takes into account one or more of the issues discussed above, the relationships between data, the ambiguity of meaning, and the growing volume of information, as well as possibly other issues.